Hardcopy images, such as those obtained by silver halide photography or standard lithographic processes, are typically provided in continuous tone form. However, many images are provided in halftone form i.e. pictures contained in newspaper or magazine articles as well as several types of image files that are stored in computer memory. Halftone images are binary images that have pixels that are either turned on or off. The image is printed by enabling or withholding the application of ink at locations on the copy sheet that correspond to the output of each pixel. Unfortunately, direct printing of a halftone image that has been acquired such as by scanning or similar methods is usually not desired. Moire, distortions and other artifacts are often introduced when image processing operations such as scaling, enhancement and re-halftoning are performed on halftone images. Because of this, the halftone image is usually converted to a continuous tone image, subjected to appropriate image processing, and then reconverted to a halftone image for printing. Image processing systems used with printers in reprographic systems typically require capability to convert halftone images to continuous tone images to meet these conversion and reconversion needs, to enable processing by any of a large variety of enhancement algorithms commonly available for continuous tone images. These processes are essentially estimation processes resulting in some loss of information since they cannot be reversed exactly to reproduce an image that has an exact correspondence to the original image. However, just as a halftone or dithered digital image gives a visual impression of a gray, it is possible to approximate the original continuous tone digital image using reconstructive methods.
It is a generally known procedure to reverse the digital halftone process in order to approximate a continuous tone digital image. One traditional method of reversing the halftoning process is through the application of a low-pass filter to the binary image data. Generally speaking, low-pass filter methods cannot maintain the fidelity of the edge information contained in the original image and in fact may blur edges and introduce artifacts into the continuous tone output image.
The following disclosures may be relevant to aspects of the present invention:
U.S. Pat. No. 4,194,221 to Stoffel issued Mar. 18, 1980 discloses an image data handling system to automatically detect and segregate from a stream of image pixels high frequency half-tone image input, continuous tone image input, low frequency half-tone image input, and line image input which may be present in the pixel stream. The image pixels are first autocorrelated in accordance with a predetermined algorithm to detect if high frequency half-tone image data is present. Data of this type found is processed by first descreening and then rescreening at a lower frequency to provide binary level pixels. The pixel stream is analyzed for the presence of continuous tone image data. Where found, such data is processed by a template screening process to provide binary level pixels. Remaining pixels comprising low frequency half-tone and line copy image data are thresholded to provide binary level pixels.
U.S. Pat. No. 4,630,125 to Roetling issued Dec. 16, 1986 discloses a method of reconstructing a continuous tone image of grayscale values that have been converted to a halftone image of black and white spots. The conversion to the digital halftone image spots was by comparing each pixel of the continuous tone grayscale image to a periodic screen pattern and providing either a black or white spot based on the comparison. In particular, to reconstruct the continuous tone grayscale image from the halftone image, each spot of the halftone image is isolated along with a neighborhood of surrounding spots. For each neighborhood, the maximum screen pattern value producing a white spot is compared to the minimum screen value producing a black spot. If the minimum screen value giving a black spot is greater than the maximum screen value giving a white spot, then the grayscale pixel value of the isolated spot is the average of the maximum and minimum screen values. If the minimum screen value giving a black spot is less than the maximum screen value giving a white spot, then the process is repeated after deleting that portion of the neighborhood of surrounding spots containing the maximum or minimum screen value furthest from the isolated spot.
U.S. Pat. No. 4,841,377 to Hiratsuka et al. issued Jun. 20, 1989 discloses a continuous image estimation method of a binary image wherein only one scanning aperture satisfying a predetermined condition for each picture element of a continuous image to be estimated from a plurality of scanning apertures for each kind in a dither image formed of a dither matrix, and the continuous image is estimated on the basis of the number of white or black picture elements in the scanning aperture selected. The predetermined condition is that a gradation expression is conducted in a lower spatial frequency range by using larger scanning apertures and in a higher spatial frequency range by using smaller scanning apertures, and that for the coincidence between patterns of a dither image in the scanning aperture and a binary image, which is made binary with the dither matrix from a continuous image formed on the bases of the number of the white or black picture elements in the scanning aperture, the patterns being obtained by comparing the dither image and the binary image for each aperture.
U.S. Pat. No. 5,027,078 to Fan issued Jun. 25, 1991 discloses a method of unscreening a digitally created halftone image to reconstruct a continuous tone image, including the determination of the parameters of the halftone screen used to produce the halftone image, logically filtering the halftone image to determine approximate continuous tone levels, and optionally, smoothing the continuous tone levels of the reconstructed image to minimize the quantization errors introduced during the original screening or dithering process.
U.S. Pat. No. 5,243,444 to Fan issued Sep. 7, 1993 discloses an image processing system converts unscreened and other halftone images to continuous tone images. Value data is sequentially generated for successive pixels of a screened or unscreened halftone image. Each image pixel is Sigma filtered with a predetermined set of filter parameters including the filter window size and a Sigma difference range that is applied to determine which pixels in the filter window are counted in determining average window pixel values. An output continuous tone image containing the Sigma filtered pixels is generated for storage and/or processing to a halftone copy or print.
U.S. Pat. No. 5,339,170 to Fan issued Aug. 16, 1994 discloses an image processing system which converts screen structured halftone images to continuous tone images. Value data is sequentially generated for successive pixels of a halftone image. An averaging filter is provided for sequentially filtering each pixel in the halftone image in the horizontal image direction in accordance with a first predetermined filter to generate an intermediately filtered image. A pattern matching filter then sequentially filters each pixel in the intermediately filtered image in the vertical direction to generate a hybrid filtered image. The hybrid filter arrangement is then iteratively operated for three additional sets of orthogonal directions, i.e. the vertical and horizontal directions, a first diagonal direction and a second diagonal direction, and the second and first diagonal directions. The best hybrid image is generated as an output continuous tone image for storage and/or processing to a halftone copy or print.
U.S. Pat. No. 5,343,309 to Roetling issued Aug. 30, 1994 discloses an image processing system that converts halftone images to continuous tone images. It employs an adaptive filter which processes successive pixels in an input halftone image. The adaptive filter employs a filter that is selected under feedback control from a plurality of filter sets each having a plurality of filters. The halftone image is also low-pass filtered to generate a first approximation image (FAI). A spatial gradient value is computed for each pixel in the FAI. A control operates the adaptive filter to apply one of the predetermined filters to the current pixel as a function of the associated pixel spatial gradient. An output image from the adaptive filter in a first iteration of the filtering procedure can then be applied to the input of the adaptive filter for a second adaptive filtering iteration. Pixel gradients for the second iteration are computed from the image output from the first iteration. A predetermined number of iterations are performed and the image output from the last iteration is a continuous tone image for system output.
Micelli, C. M. and Parker, J. Inverse Halftoninc, Journal of Electronic Imaging Vol. 1 No. 2 pp. 143-151, April 1992.
Schweizer, S. and Stevenson, R. Bayesian Approach to Inverse Halftoning, Proc. of SPIE Conf. on Human Vision, Vis. Proc. and Dig. Display IV, Proc. SPIE 1913, pp. 282-292, 1993.
Kim, Y., Arce, G. R. and Grabowski, N. Inverse Halftoning Using Binary Permutation Filters, Proc. IEEE Trans. Image Processing, Vol. 4, pp. 1296-1311, September 1995.
Chen, L. M. and Hang, H. M. An Adaptive Inverse Halftoning Algorithm, IEEE Trans. on Image Processing, Vol. 6, No. 8, pp. 1202-1209, 1997.
Wong, P. W. Inverse Halftoning and Kernel Estimation for Error Diffusion, IEEE Trans. Image Processing, Vol. 4, No. 4 pp. 486-498, April 1995.
All of the references cited herein are incorporated by reference for their teachings.
Accordingly, although known apparatus and processes are suitable for their intended purposes, a need remains for a simple and efficient method and apparatus for converting halftone digital image data to continuous tone data.